P-HAF: Homography Estimation using Partial Local Affine Frames

Daniel Barath


We propose an algorithm, called P-HAF, to estimate planar homographies using partially known local affine transformations. This general theory is able to exploit the affine components obtained by the commonly used partially affine covariant detectors, such as SIFT or SURF, in a real time capable way. P-HAF as a minimal solver can estimate the homography using two SIFT correspondences, moreover, it can deal with any number of point pairs as an overdetermined system. It is validated both on synthesized and publicly available datasets that exploiting all information leads to more accurate estimates and makes multi-homography estimation less ambiguous.


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Paper Citation

in Harvard Style

Barath D. (2017). P-HAF: Homography Estimation using Partial Local Affine Frames . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-227-1, pages 227-235. DOI: 10.5220/0006130302270235

in Bibtex Style

author={Daniel Barath},
title={P-HAF: Homography Estimation using Partial Local Affine Frames},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)},

in EndNote Style

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)
TI - P-HAF: Homography Estimation using Partial Local Affine Frames
SN - 978-989-758-227-1
AU - Barath D.
PY - 2017
SP - 227
EP - 235
DO - 10.5220/0006130302270235